An input signal is converted from some continuosly varying physical
value (e.g. pressure in air, or frequency or wavelength of light), by
some electro-mechanical device into a continuously varying electrical
signal. This signal has a range of amplitude, and a range of
frequencies that can present. This continuously varying electrical
signal can then be converted to a sequence of digital values,
called samples, by some analog to digital conversion circuit. Figure
4.2 illustrates this process.

Figure 4.2:
Sampling a Continuous Signal

There are two factors which determine the accuracy with which the
digital sequence of values captures the original continuous signal:
the maximum rate at which we sample, and the number of bits used in
each sample. This latter value is known as the quanisation level, and
is illustrated in figure 4.3.

Figure 4.3:
Quantisation of Samples

The raw (un-compressed)
digital data rate associated with a signal then is simply the sample
rate times the number of bits per sample. To capture all possible
frequencies in the original signal, Nyquist's theorem shows that the
digital rate must be twice the highest frequency component in the
continuous signal. However, it is often not necessary to capture all
frequencies in the original signal - for example, voice is
comprehensible with a much smaller range of frequencies than we can
actually hear. When the sample rate is much lower than the highest
frequency in the continuosu signal,
a band-pass filter which only allows frequencies in the range actually
needed, is usally put before the sampling circuit. This
avoids possible ambiguous samples (``aliases'').